The economic production lot size model under volume flexibility
Computers and Operations Research
Chance constrained programming with fuzzy parameters
Fuzzy Sets and Systems
The fuzzy Riemann integral and its numerical integration
Fuzzy Sets and Systems
Fuzzy Sets and Systems
Genetic Algorithms Plus Data Structures Equals Evolution Programs
Genetic Algorithms Plus Data Structures Equals Evolution Programs
An optimal ordering and recovery policy for reusable items
Computers and Industrial Engineering - Supply chain management
Lot-sizing for inventory systems with product recovery
Computers and Industrial Engineering
Fuzzy differential equations and the extension principle
Information Sciences: an International Journal
Computers and Industrial Engineering
A note on "Fuzzy differential equations and the extension principle"
Information Sciences: an International Journal
Comparation between some approaches to solve fuzzy differential equations
Fuzzy Sets and Systems
Fuzzy Preference Ordering of Interval Numbers in Decision Problems
Fuzzy Preference Ordering of Interval Numbers in Decision Problems
Information Sciences: an International Journal
Fuzzy inventory model with two warehouses under possibility constraints
Fuzzy Sets and Systems
Mathematical and Computer Modelling: An International Journal
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A two warehouse production-recycling system for a single item with stock-dependent demand is considered. Item is produced at a production plant situated at a market place having sufficiently large warehouse with a small decorated showroom. Units are continuously transformed from production center to a showroom at the market for sale and excess units are stored at the production center warehouse. Production is stopped at regular intervals and after some production cycles, recycling process is commissioned. Used units are collected from the customers (up to beginning of last recycling cycle) at a demand-dependent fuzzy rate and then repaired to new condition before being sold again. Model is formulated using fuzzy differential equation and @a-cut of fuzzy average profit is obtained. In the first approach, Modified Graded Mean Integration Value (MGMIV) of the average profit is optimized to derive decisions for the decision maker (DM). A genetic algorithm with binary mode representation, Roulette wheel selection and random mutation process is used to solve the model. In the second approach, using fuzzy preference ordering of intervals (FPOIs), @a-cut of fuzzy average profit is optimized using the above GA to derive optimum decisions for DM. The proposed models are illustrated with numerical examples.